Antibiotic-resistant bacterial infections, in acute cases like sepsis and others, result in costing the US billions of dollars in healthcare costs. Estimates vary but have ranged as high as $20 billion in excess direct healthcare costs, with additional costs to society for lost productivity as high as $35 billion a year (2008 dollars)1. The prevailing view is that the widespread misuse of antibiotics over the last few decades has allowed bacteria to evolve and develop defenses to neutralize or resist antibiotics. Antibiotic-resistant bacterial infections are spreading at a phenomenal rate and seriously threaten human survival and severely set back medical progress made in the last century2.
Today, clinical treatment of bacterial infections, especially in acute cases of sepsis, requires multiple steps including (AST). Conventionally, AST requires time-intensive culturing techniques, such as disk-diffusion3 and broth-dilution4, which can take up to two days for the bacteria to grow to an appropriate density for clinical assessment. In addition to being time consuming, such AST techniques are limited to cultivable strains of bacteria, leading to delayed administration of appropriate antibiotics that often results in putting patients at risk. Appropriate antibiotic regimens can be unduly delayed, especially for slow-growing and non-cultivable microorganisms. A faster AST is needed to reduce morbidity and mortality rates significantly.
With an increasing clinical demand for AST, multiple methodologies have been developed to characterize antibiotic activity on bacterial metabolism. Examples include the measurement of incremental increases in cell length and number.5,8 While these approaches have met with some degree of success, they still rely on culturing, which is not universally applicable, especially to non-cultivable microorganisms and anaerobes, new bacterial strains, and slow-growing bacteria.11 
Techniques, such as magnetic beads5,6 and optical imaging,7,8 have been used to measure cell growth by proxy means, recording changes in vibrational amplitude or image intensity. While these alternative techniques meet some requirements, they are still time-consuming and semi-quantitative since they require the bacteria to be grown to high density. More recently, micro-cantilever deflections have been used as metabolic sensors to detect bacterial cell motion.9,10 In the case of atomic force microscope (AFM) cantilevers, one major disadvantage is the lack of means to differentiate strains and obtain strain-specific susceptibility results. This cantilever approach would be difficult to use when a patient has a polymicrobial infection.
Thus, for humans to win the evolutionary battle between our wits and microbial genes, there is a crucial need for point-of-care technologies that can rapidly generate antibiotic susceptibility profiles of an infecting pathogen, ideally at the earliest stages of disease. Fast generation of antibiotic susceptibility profiles would allow administration of appropriate narrow-spectrum/personalized therapies at the earliest possible stage. Automated, and more universal technologies for antibiotic susceptibility testing (AST), are needed to replace current culture-based approaches. Such a technology would also be applicable to non-cultivable and slow growing microbial species and considerably reduce time required to obtain a susceptibility report.
The present invention overcomes the limitations inherent in the known methods described above. Disclosed herein for the first time is an AST tool based on a plasmonic imaging technology for simultaneous and rapid measurement of the binding kinetics and treatment effects of antibiotics on bacteria in a culture-free environment. This novel AST method can quickly detect antibiotic resistant strains and improve clinical diagnoses.